OBJECTIVE: To compare the estimated effects of dialysis center profit status on patient survival using alternative estimation strategies with retrospective data. DATA SOURCES/STUDY SETTING: Patient and provider-level retrospective data from the United States Renal Data System (USRDS), 1996-1999. STUDY DESIGN: Observational risk adjustment and instrumental variable methods. DATA COLLECTION/EXTRACTION METHODS: Study collected measures from various USRDS files describing clinical characteristics, survival, and the profit status of the initial dialysis center for incident end-stage renal disease (ESRD) patients aged 67+. USRDS facility files were used to assess dialysis center profit status and measure patient distances to dialysis centers. PRINCIPAL FINDINGS: Found survival effect related to profit status in the range of previous research using risk-adjusting covariates similar to those used in previous models. Adding further risk-adjusting covariates halved this effect. The relative proximity of for-profit and nonprofit dialysis centers to the patient residence was the strongest determinant of the profit status of the patient's initial dialysis center. The effect of profit status on survival was eliminated using the two-stage least squares variant of instrumental variable estimation with the relative proximity of for-profit and nonprofit dialysis centers to the patient's residence as the instrument. CONCLUSIONS: Using only the variation in initial dialysis center profit status that was related to the relative proximity of for-profit and nonprofit dialysis centers to the patient, we found no relationship between dialysis center profit status and patient survival. These results are in contrast to results obtained using risk-adjustment methods with a limited set of risk-adjusting covariates.
OBJECTIVE: To compare the estimated effects of dialysis center profit status on patient survival using alternative estimation strategies with retrospective data. DATA SOURCES/STUDY SETTING:Patient and provider-level retrospective data from the United States Renal Data System (USRDS), 1996-1999. STUDY DESIGN: Observational risk adjustment and instrumental variable methods. DATA COLLECTION/EXTRACTION METHODS: Study collected measures from various USRDS files describing clinical characteristics, survival, and the profit status of the initial dialysis center for incident end-stage renal disease (ESRD) patients aged 67+. USRDS facility files were used to assess dialysis center profit status and measure patient distances to dialysis centers. PRINCIPAL FINDINGS: Found survival effect related to profit status in the range of previous research using risk-adjusting covariates similar to those used in previous models. Adding further risk-adjusting covariates halved this effect. The relative proximity of for-profit and nonprofit dialysis centers to the patient residence was the strongest determinant of the profit status of the patient's initial dialysis center. The effect of profit status on survival was eliminated using the two-stage least squares variant of instrumental variable estimation with the relative proximity of for-profit and nonprofit dialysis centers to the patient's residence as the instrument. CONCLUSIONS: Using only the variation in initial dialysis center profit status that was related to the relative proximity of for-profit and nonprofit dialysis centers to the patient, we found no relationship between dialysis center profit status and patient survival. These results are in contrast to results obtained using risk-adjustment methods with a limited set of risk-adjusting covariates.
Authors: Nina R Joyce; Thomas G McGuire; Stephen J Bartels; Susan L Mitchell; David C Grabowski Journal: Health Serv Res Date: 2018-05-07 Impact factor: 3.402
Authors: Bianca K Frogner; Kenneth Harwood; C Holly A Andrilla; Malaika Schwartz; Jesse M Pines Journal: Health Serv Res Date: 2018-05-23 Impact factor: 3.402
Authors: Ellen C Caniglia; Rebecca Zash; Sonja A Swanson; Kathleen E Wirth; Modiegi Diseko; Gloria Mayondi; Shahin Lockman; Mompati Mmalane; Joseph Makhema; Scott Dryden-Peterson; Kalé Z Kponee-Shovein; Oaitse John; Eleanor J Murray; Roger L Shapiro Journal: Am J Epidemiol Date: 2019-09-01 Impact factor: 4.897